The present invention relates generally to computer vision and pattern recognition, and in particular to video analysis for detecting the presence of fire.
The ability to detect the presence of fire provides for the safety of occupants and property. In particular, because of the rapid expansion rate of a fire, it is important to detect the presence of a fire as early as possible. Traditional means of detecting fire include particle sampling (i.e., smoke detectors) and temperature sensors. While accurate, these methods include a number of drawbacks. For instance, traditional particle or smoke detectors require smoke to physically reach a sensor. In some applications, the location of the fire or the presence of heating, ventilation, and air conditioning (HVAC) systems prevents smoke from reaching the detector for an extended length of time, allowing the fire time to spread. A typical temperature sensor requires the sensor to be located physically close to the fire, because the temperature sensor will not sense a fire until a sufficient amount of the heat that the fire produces has spread to the location of the temperature sensor. In addition, neither of these systems provides as much data as might be desired regarding size, location, or intensity of the fire.
Video detection of a fire provides solutions to some of these problems. A number of video content analysis algorithms for detecting flame (as indicative of fire) are known in the prior art. For example, some algorithms analyze video data to detect color characteristics (e.g., red, orange) associated with flame. These algorithms may also analyze the video data for flicker characteristics indicative of flame. However, positively indicating the presence of a fire typically requires some overlap between regions in the image illustrating both characteristics of flame. In addition, while these methods detect the presence of flame, they do not detect the presence of smoke.